In a multiple regression analysis, two independent variables are considered and the sample size is 26. The regression coefficients and the standard errors are as follows; b1 = 1.468 sb1 = 0.89 b2 = -1.084 sb2 = 0.88 Use the 0.05 significance level; Conduct a test hypothesis to determine whether either independent variable has a coefficient equal to 0. (negative amounts should be indicated by a minus sign) (round to 3 decimal places) Would you consider deleting either variable from the regression equation?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
In a multiple
| b1 = 1.468 | sb1 = 0.89 |
| b2 = -1.084 | sb2 = 0.88 |
Use the 0.05 significance level;
- Conduct a test hypothesis to determine whether either independent variable has a coefficient equal to 0. (negative amounts should be indicated by a minus sign) (round to 3 decimal places)
- Would you consider deleting either variable from the regression equation?
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